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Proceedings Paper

Using sound to extract meaning from complex data
Author(s): Carla Scaletti; Alan B. Craig
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Paper Abstract

In analyzing abstract data sets, it is useful to represent them in several alternative formats, each format bringing out different aspects of the data. While most work in data mapping has focused on visual representations, it has been found that sonic representations can also be effective aids in interpreting complex data, especially when sonification is used in conjunction with visualization. The authors have developed prototypes for several high-level sonification tools that can be applied to a wide variety of data. While they used programmable multi- processor digital signal processing hardware to develop and experiment with these prototypes, each of these tools could be implemented as special-purpose hardware or software for use by scientists in specific applications. The prototype tools include: Mapper (maps data to various sonic parameters), Comparator (feeds a different mapping into each speaker channel), Sonic Histogram (maps the magnitude of each category onto the amplitude of its associated sound), Shifter (shifts signals into the audible range), Marker (a sonic alarm that marks a specific condition). These tools were tested by using them to generate data-driven sound tracks for video animations generated from the same data. The resulting videos provide an increased data bandwidth and an increased sense of virtual reality to the viewer.

Paper Details

Date Published: 1 June 1991
PDF: 13 pages
Proc. SPIE 1459, Extracting Meaning from Complex Data: Processing, Display, Interaction II, (1 June 1991); doi: 10.1117/12.44397
Show Author Affiliations
Carla Scaletti, Univ. of Illinois/Urbana-Champaign (United States)
Alan B. Craig, Univ. of Illinois/Urbana-Champaign (United States)

Published in SPIE Proceedings Vol. 1459:
Extracting Meaning from Complex Data: Processing, Display, Interaction II
Edward J. Farrell, Editor(s)

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